Business at the Speed of Thought: Succeeding in the Digital Economy (Penguin Business Library) by Bill Gates & Collins Hemingway

Author:Bill Gates & Collins Hemingway [Gates, Bill]
Language: eng
Format: mobi
ISBN: 9780140283129
Publisher: Penguin Books Ltd
Published: 2000-05-24T14:00:00+00:00

GETTING THE MOST OUT OF DATA MINES FOR EVERYONE

Today most data mining systems are quite expensive, ranging from $25,000 to $150,000 for a small or medium-size business to millions of dollars for a high-end customer such as Wal-Mart. One insurance company spent more than $10 million for a data mining solution five years ago. The CEO said he knew he could obtain the same solution for a good deal less money with today’s technology but the results had been worth the $10 million investment. That remark gives an indication of the value of data mining, but these high prices reflect the old world order of software complexity, in which only the largest organizations, using a lot of staff or hiring specialized vendors, could make good use of data.

With the growth of competition in our information-based economy, customer data has become an increasingly important asset. Every company, and every knowledge worker at a company, has an imperative to get the most out of the company’s data assets. These new users can’t afford big database budgets or specialized database experts. Fortunately, as data mining capabilities become available on the high-volume PC platform, you’ll see prices drop dramatically and the use of data mining explode in companies and departments of all sizes. Soon every business user will be able to do the high-end analysis that used to be reserved for the companies that could shell out big bucks. Data mining will become pervasive, a standard capability of every business’s information system infrastructure.

The greatest value of data mining will be to help companies determine the right products to build and the right way to price them. Companies will be able to evaluate a variety of packaging options and price points to see which ones are most appealing to customers and profitable to themselves. Such capabilities are of special interest to companies that sell information products. Unlike a car or chair, products such as insurance, financial services, and books have far more cost tied up in development than in production and have a value determined more by the customer than by the physical cost of goods. The secret to success with information products is understanding the profile and buying habits of your most likely customer.

Insurance companies, for instance, have products that are very profitable with some customers and less profitable—or unprofitable—with others. The difference is related to loss experience with policyholder claims. Data mining can provide an insurance company with the customer profiles and geographies where its loss experience is very low or very high. The company can determine whether to do heavy marketing and attractive pricing to people in an age group or geography with good loss experience and whether to raise prices or do less marketing in groups with bad loss experience. When you have that kind of variability, it’s worth a lot to do data mining to help develop your product strategy. Banks have similar opportunities to use data mining to target new customers. People are now more willing to switch banks, and there are many new financial services companies.

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